The Dynamic Range (DR) of images of scenarios and views is defined as the ratio between the intensity of the brightest spot in the image and the minimum significant differential of intensities across the image. The image DR determines how many distinct levels of intensities a subsequent user of an image must employ in order to fully exploit the information conveyed by the image. In sensor acquired images--the minimum significant cross-image difference is bounded by the sensor noise, and on the other hand--the maximum acquirable signal is bounded by the sensor saturation level. One can thus realize that the DR of an acquired image is in fact bounded by the Saturation to Noise Ratio (SatNR) of the acquiring sensor. The DR of natural views and scenarios may exceed ten to the tenth power ( 10.sup.10). The human eye, as well as the eyes of animals, can accommodate such huge DR without too much of an apparent difficulty. This implies that the self generated noise of biological image sensors is sufficiently small compared to their saturation level, so that the SatNR can match the DR of natural views and scenarios. However, the SatNR of common electronic image sensors such as Charged Coupled Devices (CCD) does not usually exceed several hundreds, say 256. This in turn implies that all the details in the original view whose contrasts are smaller than 1/256 of the brightest spot, but still are bigger than say, ten to the minus tenth of the same, will totally disappear in the process of acquisition.
Thus, it is the purpose of many inventions including the present, to increase the DR of image sensors in order to diminish the acquisition losses as much as possible. The inherent sensor sensitivity, which is how much of electrical charge is generated by the sensor per a given number of photons that hit its receiving surface, depends on its geometric and optical properties and the quality of the materials that make it. Traditionally, the essence of the imaging process, which is to say--the conversion of images from levels of light intensities into levels of readable electrical charges or voltages--is the exposure of an appropriate array of sensors to an adequately focused image for a prescribed period of time, letting those sensors collect photons and convert them into electrical charges. With time those charges are accumulated, so that at the end of the exposure interval the amount of the net accumulated charge at a particular sensor reflects the magnitude of the photon flux, or the light intensity that belongs to the spot of the image that has been focused on that particular sensor. An obvious way to influence the sensors responsivity to light flux, is varying the exposure time interval, also referred to as "The Integration Time". Another obvious such way is to change the sensor optical aperture. Increasing the exposure time and/or the aperture enable the sensors to integrate more photons at every spot in the field of view, hence causes a proportional increase of the accumulated charges. However, besides other side effects of overly increased exposure interval and aperture size, there is a maximum amount of charge that a light cell can hold. When this maximum level is reached in a certain cell, it becomes saturated and ceases to reflect the light variations of the original view. At this point this cell can not function as an imaging device anymore. It is commonly said that the whole image is in saturation when considerable areas of neighboring cells are saturated, causing these areas of the output image to appear as white uniform zones that do not show any of the original view. The only way to increase the DR of an image sensor of a given sensitivity, is to increase its maximum Signal to Noise Ratio (SNR). The maximum SNR of a sensor is the sensor Saturation to Noise Ratio (SatNR). Thus, in order to increase the DR of a sensor one can either try to increase its saturation level, or one can try to reduce the sensor self generated noise. There are two principle kinds of self generated noise:
a). Temporal noise, a stochastic process that depends mainly on the size and temperature of the active part of the sensor, and PA1 b). A so called "Fixed Pattern Noise" that is associated with sensors that consist of arrays of image detectors, also called "Light Cells". Most of the fixed pattern noise is originated in the initial, or bias voltage that a light cell may have prior to its exposure to light. In arrays of sensors those bias voltages may vary from one sensor to another, so that the exposure of the array to an absolutely uniform, so called "Flat Field" input image, will still result in a non uniform output image that merely reflects the variations in the sensors bias terms. Reduction of temporal noise is done by reducing either, or both the sensor size and its operating temperature. Reduction of the fixed pattern noise is done traditionally by improving the uniformity between the light cells inside the array, and by using various methods of subtraction or compensation of the fixed pattern, or as it also called, the flat field image.